Search is changing fast and most SEO strategies haven’t caught up.

Google AI Overviews, ChatGPT, Bing Chat, Perplexity, and voice assistants no longer show ten blue links. They give one answer.

In this video, you’ll learn:

• What Answer Engine Optimization (AEO) really is

• How AEO is different from traditional SEO

• Why traffic can drop while influence and revenue grow

• How AI decides which content becomes the answer

• The role of schema, E-E-A-T, and question-first content

• How AEO, SEO, and GEO work together

• Practical steps to optimize for AI search and zero-click results

If you’re an SEO professional, content marketer, or founder and your content isn’t showing up in AI responses, this video will show you exactly what to fix.

Search isn’t dying.

It’s becoming answer-first.

Search has changed — and most marketers haven’t noticed yet.

Users are no longer clicking through search results.

They’re asking ChatGPT, Google Gemini, and Perplexity… and getting instant answers.

So the real question is:

When AI answers, does it mention your brand?

In this video, I break down Generative Engine Optimization (GEO) — the next evolution of SEO — and explain how to optimize your content so AI systems retrieve, trust, and cite it inside generated answers.

You’ll learn:

• What GEO is and how it differs from traditional SEO

• How ChatGPT, Google Gemini, and Perplexity actually source answers

• Why rankings alone are no longer enough

• Content structures AI engines prefer

• Practical GEO tactics you can apply immediately

• The biggest mistakes marketers make with AI search

This video is for SEO professionals, content marketers, founders, and product leaders who want to stay visible in an AI-first search world.

If SEO drives clicks, GEO drives citations.

Watch till the end to future-proof your search strategy.

#GEO #GenerativeEngineOptimization #SEO #AISEO #AIsearch #ChatGPT #GoogleGemini #PerplexityAI #DigitalMarketing #ContentStrategy #SearchMarketing #FutureOfSearch

Most SaaS products fail with AI not because the models are weak, but because the problems are poorly chosen.

In this video, I break down a clear, product-led framework to identify where AI actually adds value in SaaS products. You’ll learn how to audit your product workflows, spot high-impact AI use cases, and avoid building AI features that look impressive but don’t move real metrics.

We’ll cover:

• How to find AI opportunities by studying user workflows

• Repetitive and data-heavy tasks that are perfect for AI

• Using AI for personalization and recommendations

• Turning product data into predictive insights like churn and forecasting

• When to build AI-native features like assistants or chatbots

• How to validate AI ideas quickly with prototypes

If you’re a product manager, SaaS founder, or product leader thinking about AI, this video will help you focus on the right problems before writing a single line of code.